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» Application of Fuzzy Rule Induction to Data Mining
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2005
IEEE
14 years 2 months ago
A pipelined data-parallel algorithm for ILP
The amount of data collected and stored in databases is growing considerably for almost all areas of human activity. Processing this amount of data is very expensive, both humanly...
Nuno A. Fonseca, Fernando M. A. Silva, Víto...
CORR
2010
Springer
208views Education» more  CORR 2010»
13 years 8 months ago
Discovering potential user browsing behaviors using custom-built apriori algorithm
Most of the organizations put information on the web because they want it to be seen by the world. Their goal is to have visitors come to the site, feel comfortable and stay a whi...
Sandeep Singh Rawat, Lakshmi Rajamani
ACSC
2005
IEEE
14 years 2 months ago
The Electronic Primaries: Predicting the U.S. Presidency Using Feature Selection with Safe Data Reduction
The data mining inspired problem of finding the critical, and most useful features to be used to classify a data set, and construct rules to predict the class of future examples ...
Pablo Moscato, Luke Mathieson, Alexandre Mendes, R...
NIPS
2007
13 years 10 months ago
Regularized Boost for Semi-Supervised Learning
Semi-supervised inductive learning concerns how to learn a decision rule from a data set containing both labeled and unlabeled data. Several boosting algorithms have been extended...
Ke Chen 0001, Shihai Wang
DKE
2002
218views more  DKE 2002»
13 years 8 months ago
Computing iceberg concept lattices with T
We introduce the notion of iceberg concept lattices and show their use in knowledge discovery in databases. Iceberg lattices are a conceptual clustering method, which is well suit...
Gerd Stumme, Rafik Taouil, Yves Bastide, Nicolas P...